L1-Norm Regularized Deconvolution of Functional MRI BOLD Signal
Abstract
Deconvolution methods are used to denoise the blood oxygen level-dependent (BOLD) response, the signal that forms
the basis of functional MRI (fMRI). In this work we propose a novel approach based on a temporal regularized deconvolution of the BOLD fMRI signal with the least absolute shrinkage and selection operator (LASSO) model, solved using the angle regression algorithm (LARS). In this way we were able to recover the underlying neurons activations and their dynamics
Domains
Signal and Image Processing| Origin | Files produced by the author(s) |
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